With the large amounts of data generated in recent years, data mining and machine learning are playing an increasingly important role in today's computing environment. For example, businesses may utilize either data mining or machine learning to predict the behavior of users. This predicted behavior may then be used by businesses to determine which plan to proceed with, or how to grow the business.
The data used in data mining and analytics is typically not stored in a uniform data storage system. Many data storage systems utilize different file systems, and those different file systems are typically not compatible with each other. Further, the data may reside in geographically diverse locations.
One conventional method to performing data analytics across different databases includes copying data from one database to a central database, and performing the data analytics on the central database. However, this results in an inefficient use of storage space, and creates issues with data consistency between the two databases.
There is a need, therefore, for an improved method, article of manufacture, and apparatus for managing data.